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Entropy02:39

Entropy

29.4K
Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
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Third Law of Thermodynamics02:38

Third Law of Thermodynamics

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A pure, perfectly crystalline solid possessing no kinetic energy (that is, at a temperature of absolute zero, 0 K) may be described by a single microstate, as its purity, perfect crystallinity,and complete lack of motion means there is but one possible location for each identical atom or molecule comprising the crystal (W = 1). According to the Boltzmann equation, the entropy of this system is zero.
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Entropy within the Cell01:22

Entropy within the Cell

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A living cell's primary tasks of obtaining, transforming, and using energy to do work may seem simple. However, the second law of thermodynamics explains why these tasks are harder than they appear. None of the energy transfers in the universe are completely efficient. In every energy transfer, some amount of energy is lost in a form that is unusable. In most cases, this form is heat energy. Thermodynamically, heat energy is defined as the energy transferred from one system to another that...
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Entropy and the Second Law of Thermodynamics01:20

Entropy and the Second Law of Thermodynamics

2.8K
The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
The relation  between entropy and disorder can be illustrated with the example of the phase change of ice to water. In ice, the molecules are located at specific sites giving a solid state, whereas, in a liquid form, these molecules are much freer to move. The molecular arrangement has therefore become more randomized. Although the change in average...
2.8K
Entropy and Solvation02:05

Entropy and Solvation

7.0K
The process of surrounding a solute with solvent is called solvation. It involves evenly distributing the solute within the solvent. The rule of thumb for determining a solvent for a given compound is that like dissolves like. A good solvent has molecular characteristics similar to those of the compound to be dissolved. For example, polar solutions dissolve polar solutes, and apolar solvents dissolve apolar solutes. A polar solvent is a solvent that has a high dielectric constant (ϵ...
7.0K
The Second Law of Thermodynamics01:14

The Second Law of Thermodynamics

5.3K
In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Scientists refer to the measure of randomness or disorder within a system as entropy. High entropy means high disorder and low energy. To better understand entropy, think of a student’s bedroom. If no energy or work were put into it, the room would quickly become messy. It would exist in a very disordered state, one of high entropy. Energy must be...
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Related Experiment Video

Updated: Jun 26, 2025

Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes
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From Local Atomic Environments to Molecular Information Entropy.

Alexander Croy1

  • 1Institute of Physical Chemistry, Friedrich Schiller University Jena, 07737 Jena, Germany.

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|May 13, 2024
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Summary

We introduce an information entropy approach to quantify molecular complexity and similarity. This method connects local atomic environments, enabling new applications in computational chemistry and material science.

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Area of Science:

  • Computational chemistry
  • Material science
  • Machine learning
  • Chemical informatics

Background:

  • Local atomic environment similarity is crucial for machine learning in chemistry and materials.
  • Quantifying molecular complexity and similarity is essential for predicting properties and designing new materials.

Purpose of the Study:

  • To establish a connection between information entropy and molecular similarity matrices.
  • To propose entropy as a measure of molecular complexity and a tool for comparing molecules in mixtures.

Main Methods:

  • Calculating molecular entropy based on local atomic environment similarity.
  • Utilizing SMILES representations and the SOAP kernel for similarity definitions.
  • Analyzing entropy changes in molecular mixtures to assess molecular similarity.

Main Results:

  • Developed an entropy-based measure for molecular complexity.
  • Demonstrated good agreement between different similarity-based entropy calculations by tuning parameters.
  • Showcased the utility of mixing entropy as a molecular similarity metric.

Conclusions:

  • The information entropy provides a versatile measure for molecular complexity and similarity.
  • The proposed approach connects various similarity metrics and shows broad applicability in computational chemistry and material science.